1. Field of Invention
The present disclosure relates to the digital scanning or recording of original images, as would be found, for example, in a scanner, digital copier, facsimile, or multifunction machine.
2. Description of Related Art
Digital scanning, or the recording of images from original documents as digital image data, has become prevalent in both office and home environments. Digital scanning is generally performed on equipment having scanning capabilities, such as a scanner, digital copier, facsimile, or multifunction machine. In the case of a scanner, for example, the original documents bearing content to be imaged as digital data, are loaded onto the scanner glass, which is sized to handle a variety of document sizes. To capture the image, the scanner employs a scanning imaging device, such as, for example, an image sensor that may include one or more linear arrays of photo-sensors. Each of the photo-sensors records the reflected light from a series of small areas in the original document as the photo-sensors move past the document, yielding a set of digital signals comprising intensity and tonal values for each pixel of the image.
During the scanning process, the scanner typically performs a pre-scan operation that captures a reduced, resolution image of the original document, at the full scanner capacity size, to produce a preview image. As depicted in FIG. 1A, the reduced resolution preview image 110 includes a portion representing the contents of the original document 112 as well as a horizontal portion 114j and vertical portion 114i that represents the imaged white platen areas scanner back-cover (i.e., scanner capacity size).
The preview image 110 is processed with an automatic page size detection algorithm to determine a document page size. The resulting page size is then used to control the scanner as it performs a full resolution scan of the original document.
As a practical matter, the scanning of original images involves certain considerations to provide a satisfactory result. One set of considerations involves taking into account the size of the original documents being scanned. For scanning applications, it is desirable that the scanner automatically determine the size of the original document, so that it only captures the desired image of the original document, while excluding the rest of white platen back-cover area of the scanner.
With this said, it is to be noted that conventional automatic page size detection algorithms are only based on very localized page edge detection schemes that operate on the content of the reduced resolution pre-scan image to locate a page edge as opposed to detecting the actual page edge. For example, to find the right page edge under such schemes, a local edge detection operator is applied at each row to locate the most-right edge based on the imaged content of the document. After finding the most-right edge of each row, the algorithm tracks the edge points with some edge point local continuity condition from top to bottom. And the location of the survived most-right edge point at the end will be used to compute the page width. The final image is then cropped out from the whole image, based on the computed image size.
There are two drawbacks to this approach. First, the approach is vulnerable to scanner noise caused by dirt on the scanner glass between scanner imaging device, such as the image sensor, and the original documents. It is fairly common to have some small dust particles or short paper fiber residue on the scanner glass and, although such particles and/or residue maybe appear small to the naked eye, it can easily extend more than a couple of pixels at common pre-scan resolution (e.g., 150 dpi). This may mislead local edge point detection and tracking algorithms. The page edge itself, which is formed at the boundary between page white and platen back-cover, which is white for most cases, is a “weak” edge. If stronger edge detection conditions are applied to avoid dots or short thin line caused by the dirt on the glass, which usually has the same order to even greater edge strength compared to the page edge, it may also miss more locations of the true page edge point of each row. In contrast, if one applies weaker edge detection condition, then the tracking algorithm becomes more susceptible to artificial edges formed by the dirt.
Second, if the original document size reaches the full width of the scanner capability, there may be no page edge at the right. In this case, the conventional algorithms will not be able to detect the paper width correctly. For a typical document, such algorithms usually set the page width at the last strong and continuous edge inside the image contents of the original document, which may exclude some portions of the original image contents.